U.S. patent application number 15/760596 was filed with the patent office on 2020-07-30 for tomography apparatus and controlling method for the same.
The applicant listed for this patent is Samsung Electronics Co., Ltd. Invention is credited to Narayanan AJAY, Toshihiro RIFU, Jong Hyon YI, Alexander ZAMYATIN.
Application Number | 20200240934 15/760596 |
Document ID | 20200240934 / US20200240934 |
Family ID | 1000004797007 |
Filed Date | 2020-07-30 |
Patent Application | download [pdf] |
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United States Patent
Application |
20200240934 |
Kind Code |
A1 |
YI; Jong Hyon ; et
al. |
July 30, 2020 |
TOMOGRAPHY APPARATUS AND CONTROLLING METHOD FOR THE SAME
Abstract
Disclosed is a tomography apparatus including a controller for
estimating a Point Spread Function (PSF) corresponding to a
location of an object; and an image processor for de-blurring
projection data of the object based on the PSF corresponding to the
location of the object.
Inventors: |
YI; Jong Hyon; (Yongin-si,
KR) ; RIFU; Toshihiro; (Suwon-si, KR) ; AJAY;
Narayanan; (Suwon-si, KR) ; ZAMYATIN; Alexander;
(Suwon-si, KR) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Samsung Electronics Co., Ltd |
Suwon-si |
|
KR |
|
|
Family ID: |
1000004797007 |
Appl. No.: |
15/760596 |
Filed: |
April 4, 2016 |
PCT Filed: |
April 4, 2016 |
PCT NO: |
PCT/KR2016/003452 |
371 Date: |
March 15, 2018 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61B 6/54 20130101; G01N
23/046 20130101; G06T 5/20 20130101; G06T 7/0012 20130101; G01N
2223/401 20130101; G06T 5/003 20130101; G06T 11/008 20130101; G06T
7/70 20170101; G06T 2207/10116 20130101; A61B 6/032 20130101; A61B
6/583 20130101; A61B 6/4291 20130101 |
International
Class: |
G01N 23/046 20060101
G01N023/046; G06T 11/00 20060101 G06T011/00; G06T 5/00 20060101
G06T005/00; G06T 5/20 20060101 G06T005/20; G06T 7/70 20060101
G06T007/70; G06T 7/00 20060101 G06T007/00 |
Foreign Application Data
Date |
Code |
Application Number |
Sep 15, 2015 |
KR |
10-2015-0130334 |
Jan 20, 2016 |
KR |
10-2016-0006771 |
Claims
1. A tomography apparatus comprising: a controller configured to
estimate a Point Spread Function (PSF) corresponding to a location
of an object; and an image processor configured to de-blur
projection data of the object based on the PSF corresponding to the
location of the object.
2. The tomography apparatus of claim 1, wherein the controller is
configured to estimate the PSF corresponding to a distance between
an X-ray generator and the object.
3. The tomography apparatus of claim 1, wherein the controller is
configured to estimate a PSF corresponding to a channel in which
the object is located among a plurality of channels formed between
an X-ray generator and an X-ray detector.
4. The tomography apparatus of claim 1, wherein the controller is
configured to estimate the PSF based on projection data of a sample
object and geometric information of the sample object.
5. The tomography apparatus of claim 4, wherein the geometric
information comprises outline information of the sample object.
6. The tomography apparatus of claim 1, wherein the image processor
is configured to de-blur the projection data scanned at a rotation
angle of a gantry.
7. The tomography apparatus of claim 6, wherein the image processor
is configured to: obtain a plurality of projection data
corresponding to a plurality of rotation angles; and perform
de-blurring on the projection data corresponding to each rotation
angle.
8. The tomography apparatus of claim 2, wherein the controller is
configured to determine the distance between the X-ray generator
and the object based on a cross-sectional image of a sample object
scanned at a position.
9. The tomography apparatus of claim 3, wherein the controller is
configured to determine a channel in which the object is located
among the plurality of channels formed between the X-ray generator
and the X-ray detector based on a cross-sectional image of a sample
object scanned at a position.
10. The tomography apparatus of claim 1, further comprising a
storage configured to store the PSF, wherein the storage is
configured to store a plurality of PSFs mapped to different
positions of the object.
11. A method for controlling a tomography apparatus comprising:
estimating a Point Spread Function (PSF) corresponding to each
location of an object; and de-blurring projection data of the
object based on the PSF corresponding to the location of the
object.
12. The method of claim 11, wherein estimating the PSF
corresponding to each location of the object comprises estimating a
PSF corresponding to a distance between an X-ray generator and the
object.
13. The method of claim 11, wherein estimating the PSF
corresponding to each location of an object comprises estimating a
PSF corresponding to a channel in which the object is located among
a plurality of channels formed between an X-ray generator and an
X-ray detector.
14. The tomography apparatus of claim 1, further comprising: an
adaptive filter configured to correct the PSF estimated by the
controller, wherein the adaptive filter corrects the PSF depending
on a location of a region of interest.
15. The tomography apparatus of claim 14, wherein the PSF estimated
by the controller is a first PSF, and wherein the adaptive filter
generates a second PSF based on a distance from a center of a Field
of View (FOV) to the region of interest and a distance from a focal
point of X-ray radiation.
16. The method of claim 11, wherein estimating the PSF
corresponding to each location of the object comprises estimating
the PSF based on projection data of a sample object and geometric
information of the sample object.
17. The method of claim 16, wherein the geometric information
comprises outline information of the sample object.
18. The method of claim 11, wherein de-blurring projection data of
the object comprises de-blurring the projection data scanned at a
rotation angle of a gantry.
19. The method claim 19, further comprising: obtaining a plurality
of projection data corresponding to a plurality of rotation angles;
and perform de-blurring on the projection data corresponding to
each rotation angle.
20. The method of claim 12, wherein determining the distance
between the X-ray generator and the object is based on a
cross-sectional image of a sample object scanned at a position.
Description
CROSS-REFERENCE TO RELATED APPLICATION(S)
[0001] The present application claims priority under 35 U.S.C.
.sctn. 365 to International Patent Application No.
PCT/KR2016/003452 filed Apr. 4, 2016, which claims priority to
Korean Patent Application Nos. 10-2015-0130334 filed Sep. 15, 2015
and 10-2016-0006771 filed Jan. 20, 2016, each of which are
incorporated herein by reference into the present disclosure as if
fully set forth herein.
TECHNICAL FIELD
[0002] Embodiments of the present disclosure relate to a tomography
apparatus and method for controlling the same.
BACKGROUND
[0003] A medical imaging device is equipment for obtaining an image
of an internal structure of an object. A medical image processing
device is a non-invasive diagnostic device for scanning and
processing structural details, internal tissues, and fluid flow in
the body, and displaying them to the user. The user, e.g., a doctor
may diagnose a health condition and illness of a patient using the
medical image output from the medical image processing device.
[0004] As a typical device for scanning an object by X-ray
radiation to a patient, there may be a Computed Tomography (CT)
scanner.
[0005] The CT scanner corresponding to a tomography apparatus among
various medical image processing devices is widely used for close
examination of an illness, because it is capable of providing
cross-sectional images of the object and represent the internal
structure of e.g., an organ, such as kidneys, lungs, etc. in a
non-overlapping way. A medical image obtained by the tomography
apparatus is hereinafter referred to as a scanned image.
[0006] In obtaining the scanned image, the tomography apparatus is
used to perform tomographic scanning on the object to obtain law
data. Furthermore, the tomography apparatus performs certain
pre-processing on the raw data to obtain projection data. The
projection data may be a set of raw data scanned at one scanning
angle. In other words, a set of raw data simultaneously obtained at
the same scanning angle for all the channels is called the
projection data.
[0007] As the tomography apparatus or an object subject to the
tomographic scanning moves or due to the performance of the
tomography device, blurring artifacts may be created in restoring
the scanned image. For example, the blurring artifact may be
created due to limits of performance, such as the size of a focal
point of X-ray radiation, the size of an X-ray detector, the number
of images obtained per rotation of the gantry, etc.
[0008] If the blurring artifact is created, the outermost edges of
the object may be blurred and appear overlapping, and inner edges
of the object in the scanned image appear blurred.
[0009] Such a blurring artifact in a scanned image degrades image
quality of the scanned image. This may cause the user, e.g., a
doctor, to read the image incorrectly and thus diagnose an illness
inaccurately.
[0010] Accordingly, when it comes to tomographic scanning, most
important of all is to minimize the blurring artifact of a scanned
image.
SUMMARY
[0011] An object of the present disclosure is to provide a
tomography apparatus and method for controlling the same, which can
reduce blurring artifacts that might be created in a restored
scanned image.
[0012] In accordance with an aspect of the present disclosure, a
tomography apparatus is provided. The tomography apparatus includes
a controller for estimating a Point Spread Function (PSF)
corresponding to a location of an object; and an image processor
for de-blurring projection data of the object based on the PSF
corresponding to the location of the object.
[0013] The controller may estimate a PSF corresponding to a
distance between an X-ray generator and the object.
[0014] The controller may estimate a PSF corresponding to a channel
in which the object is located among a plurality of channels formed
between an X-ray generator and an X-ray detector.
[0015] The controller may estimate the PSF based on projection data
of a sample object and geometric information of the sample
object.
[0016] The geometric information may include outline information of
the sample object.
[0017] The image processor may perform de-blurring on projection
data scanned at a rotation angle of a gantry.
[0018] The image processor may obtain a plurality of projection
data corresponding to a plurality of rotation angles, and perform
de-blurring on the projection data corresponding to each rotation
angle.
[0019] The image processor may perform back projection based on the
plurality of de-blurred projection data.
[0020] The controller may determine a distance between the X-ray
generator and the object based on a cross-sectional image of a
sample object scanned at a position.
[0021] The controller may determine a channel in which the object
is located among a plurality of channels formed between the X-ray
generator and the X-ray detector based on a cross-sectional image
of a sample object scanned at a position.
[0022] The controller may estimate the PSF in the form of a
Gaussian function.
[0023] The tomography apparatus may further include a storage for
storing the PSF.
[0024] The storage may store a plurality of PSFs mapped to
different positions of the object.
[0025] The image processor may generate a scanned image based on
de-blurred projection data.
[0026] The tomography apparatus may further include a display for
displaying the scanned image.
[0027] In accordance with another aspect of the present disclosure,
a method for controlling a tomography apparatus is provided. The
method includes estimating a Point Spread Function (PSF)
corresponding to each location of an object; and de-blurring
projection data of the object based on the PSF corresponding to the
location of the object.
[0028] Estimating a PSF corresponding to each location of an object
may include estimating a PSF corresponding to a distance between an
X-ray generator and the object.
[0029] Estimating a PSF corresponding to each location of an object
may include estimating a PSF corresponding to a channel in which
the object is located among a plurality of channels formed between
an X-ray generator and an X-ray detector.
[0030] Estimating a PSF corresponding to each location of an object
may include estimating the PSF based on projection data of a sample
object and geometric information of the sample object.
[0031] De-blurring projection data of the object based on the PSF
corresponding to the location of the object may include obtaining a
plurality of projection data corresponding to a plurality of
rotation angles, and performing de-blurring on the projection data
corresponding to each rotation angle.
[0032] The method may further include performing back projection
based on the plurality of de-blurred projection data.
[0033] Estimating a PSF corresponding to each location of an object
may include determining a distance between the X-ray generator and
the object based on a cross-sectional image of a sample object
scanned at a position.
[0034] The tomography apparatus may further include an adaptive
filter for correcting an PSF estimated by the controller, and the
adaptive filter may correct the PSF depending on a location of a
region of interest.
[0035] The PSF estimated by the controller may be a first PSF, and
the adaptive filter may generate a second PSF based on a distance
from a center of a Field of View (FOV) to the region of interest
and a distance from a focal point of X-ray radiation.
[0036] The method may further include correcting the estimated PSF
before de-blurring, and correcting the estimated PSF may include
correcting the PSF depending on a location of a region of
interest.
[0037] The estimated PSF may be a first PSF, and correcting the
estimated PSF may include generating a second PSF based on a
distance from a center of a Field of View (FOV) to the region of
interest and a distance from a focal point of X-ray radiation.
[0038] According to embodiments of the present disclosure of a
tomography apparatus and method for controlling the same, blurring
artifacts created within a scanned image may be effectively
improved by creating a different PSF depending on a position of an
object.
[0039] Furthermore, according to embodiments of the present
disclosure of a tomography apparatus and method for controlling the
same, the blurring artifact created within a scanned image may be
more accurately eliminated by creating a PSF on projection data and
performing de-blurring.
BRIEF DESCRIPTION OF THE DRAWINGS
[0040] FIG. 1 is a schematic view of a Computed Tomography (CT)
scanner;
[0041] FIG. 2 is a structure of a CT scanner, according to an
embodiment of the present disclosure;
[0042] FIG. 3 shows an arrangement of a communication unit;
[0043] FIG. 4 shows views for explaining the need of accurate PSF
estimation;
[0044] FIG. 5A is a block diagram of a tomography apparatus,
according to an embodiment of the present disclosure;
[0045] FIGS. 5B and 5C are detailed views of an FOV area shown in
FIG. 2;
[0046] FIG. 6 is a view for projection data of an object created at
each rotation angle;
[0047] FIGS. 7 and 8 are views for explaining PSF;
[0048] FIG. 9 is a view for explaining how to estimate PSF;
[0049] FIG. 10 shows views for explaining a plurality of PSFs
corresponding to a plurality of beam lines and bands;
[0050] FIG. 11 is a control block diagram of a tomography apparatus
further including the adaptive filter, in accordance with another
embodiment of the present disclosure;
[0051] FIG. 12 is a view for explaining a method for an adaptive
filter to generate a second PSF;
[0052] FIG. 13 is a mimetic diagram of a sinogram, a set of a
plurality of projection data;
[0053] FIG. 14 is a view for explaining a back projection process
performed by an image processor;
[0054] FIG. 15 is a flowchart illustrating a method for controlling
a tomography apparatus, according to an embodiment of the present
disclosure;
[0055] FIG. 16 is a flowchart illustrating a method for controlling
a tomography apparatus to explain operation of S1210 in detail;
and
[0056] FIG. 17 is a flowchart illustrating a method for a
tomography apparatus to perform image processing based on estimated
PSFs.
DETAILED DESCRIPTION
[0057] Advantages, features, and methods for achieving them will be
understood more clearly when the following embodiments are read
with reference to the accompanying drawings. The embodiments of the
disclosure may, however, be embodied in many different forms and
should not be construed as limited to the embodiments set forth
herein; rather, these embodiments are provided so that this
disclosure will be thorough and complete, and will fully convey the
scope of the embodiments of the disclosure to those skilled in the
art. Like numbers refer to like elements throughout the
specification.
[0058] Terms as used herein will be described before detailed
description of embodiments of the present disclosure.
[0059] The terms are selected as common terms widely used now,
taking into account principles of the present disclosure, which may
however depend on intentions of ordinary people in the art,
judicial precedents, emergence of new technologies, and the like.
Some terms is selected at the inventor's discretion, in which case,
description thereof will be explained later in detail. Therefore,
the terms should be defined based on their meanings and
descriptions throughout the specification of the present
disclosure.
[0060] The term "include (or including)" or "comprise (or
comprising)" is inclusive or open-ended and does not exclude
additional, unrecited elements or method steps. Furthermore, the
term `unit` or `module` refers to a software or hardware component,
such as FPGA or ASIC which plays some role. However, the unit is
not limited to software or hardware. The unit may be configured to
be stored in an addressable storage medium, or to execute one or
more processors. For example, the unit may include components, such
as software components, object-oriented software components, class
components and task components, processes, functions, attributes,
procedures, subroutines, segments of program codes, drivers,
firmware, microcodes, circuits, data, databases, data structures,
tables, arrays, and variables. Functions served by components and
units may be combined into a less number of components and units,
or further divided into a more number of components and units.
[0061] Embodiments of the present disclosure will now be described
in detail with reference to accompanying drawings to be readily
practiced by an ordinary skill in the art. However, the present
disclosure may be implemented in many different forms, and not
limited to the embodiments as will be discussed herein. It should
be noted that what is irrelative to the present disclosure is
omitted from the drawings.
[0062] The term `image` as herein used may refer to
multi-dimensional data comprised of discrete image elements (e.g.,
pixels in a two dimensional (2D) image, and voxels in a three
dimensional (3D) image). For example, an image may include a
medical image of an object, which is obtained by a Computed
Tomography (CT) scanner.
[0063] The term `CT image` as herein used may refer to a composite
image of a plurality of X-ray images obtained by scanning the
object while rotating around at least one axis of the object.
[0064] The object may be a person or animal, or a part or all of
the person or the animal. For example, the object may include at
least one of organs, such as a liver, heart, uterus, breasts,
abdomen, etc., and blood veins. The `object` may also be a phantom.
The phantom may refer to a substance having a density of a living
thing and volume very close to an effective atomic number, and may
include a spherical phantom having a similar nature to a body. The
phantom may also include an image quality estimation phantom used
for estimating a quality of an image, and a calibration phantom
used for estimating a PSF.
[0065] The term `user` as herein used may be a medical expert,
e.g., a doctor, a nurse, a medical technologist, a medical image
expert, etc., or a technician who fixes medical equipment, but is
not limited thereto.
[0066] The tomography apparatus 100 may include any kind of
tomography apparatuses, such as a CT scanner, an Optical Coherence
Tomography (OCT), or Position Emission Tomography (PET) CT
scanner.
[0067] A CT scanner will now be taken as an example of the
tomography apparatus 100.
[0068] The CT scanner may provide relatively accurate
cross-sectional images of an object by obtaining and processing
image data, e.g., 2 mm or less thick, hundreds times per
second.
[0069] The CT scanner 100 in accordance with an embodiment of the
present disclosure will be described with reference to FIG. 3. The
CT scanner 100 may include various types of devices.
[0070] FIG. 1 is a schematic view of a CT scanner.
[0071] Referring to FIG. 1, the CT scanner 100 may include a data
obtainer 102, a table 105, an X-ray generator 106, and an X-ray
detector 108.
[0072] The data obtainer 102 may be a gantry, and may include the
X-ray generator 106 and the X-ray detector 108. The data obtainer
120 will now be described as the gantry.
[0073] The object 10 may be located on the table 105.
[0074] The table 105 may be moved in a certain direction (e.g., one
of up, down, left, and right directions) in the process of CT
scanning. Furthermore, the gantry 102 may also be inclined to a
certain direction to an extent of a certain angle.
[0075] FIG. 2 is a structure of a CT scanner, according to an
embodiment of the present disclosure.
[0076] The CT scanner 100 may include a gantry 102, a table 105, a
controller 118, a storage 124, an image processor 126, an input
unit 128, a display unit 130, and a communication unit 132.
[0077] As described above, the object 10 may be located on the
table 105. The table 105 in accordance with an embodiment of the
present disclosure is movable to a certain direction (e.g., one of
up, down, left, and right directions), which may be controlled by
the controller 118.
[0078] The gantry 102 in accordance with an embodiment of the
present disclosure may include a rotating frame 104, the X-ray
generator 106, the X-ray detector 108, a rotation driver 110, a
data obtaining circuit 116, and a data transmitter 120.
[0079] The gantry 102 in accordance with an embodiment of the
present disclosure may include the rotating frame 104 of a ring
form that may be rotated around a rotation axis (RA). The rotating
frame 104 may have the form of a disc as well. The rotating frame
104 may include the X-ray generator 106 and X-ray detector 108
arranged to face each other to form a field of view (FOV).
Furthermore, the rotating frame 104 may include an anti-scatter
grid 114. The anti-scatter grid 114 may be located between the
X-ray generator 106 and the X-ray detector 108. The FOV may be
divided into a Scan Field of View (SFOV) that represents the entire
scanning area from which the X-ray detector 108 may obtain an image
and a Display Field of View (DFOV) that represents a partial area
of the SFOV.
[0080] As for a medical imaging apparatus, X-ray radiation to reach
a detector (or a sensitive film) includes not only attenuated
primary radiation that forms a useful image but also scattered
radiation that lowers image quality. To transmit the majority of
the primary radiation and attenuate the scattered radiation, the
anti-scatter grid may be located between the patient and the
detector (or sensitive film).
[0081] For example, the anti-scatter grid may be constructed of
alternating strips of lead foil and interspace materials such as
solid polymer materials without cavity or solid polymers without
cavity and fiber composite materials. However, the structure of the
anti-scatter grid is not limited thereto.
[0082] The rotating frame 104 may receive a driving signal from the
rotation driver 110, and rotate the X-ray generator 106 and X-ray
detector 108 at a certain rotational speed. The rotating frame 104
may receive driving signals and power from the rotation driver 110
through a slip ring (not shown) in a way of contact. Alternatively,
the rotating frame 104 may receive driving signals and power from
the rotation driver 110 through wireless communication.
[0083] The X-ray generator 106 may receive a voltage or current
from a Power Distribution Unit (PDU, not shown) through the slip
ring and a high voltage generator (not shown) to irradiate X-rays.
When the high voltage generator applies a certain voltage
(hereinafter, referred to as a tube voltage), the X-ray generator
106 may generate X-rays having multiple energy bands in the
spectrum to correspond to the certain tube voltage.
[0084] The X-rays generated by the X-ray generator 106 may be
irradiated by a collimator 112 in a certain form.
[0085] The X-ray detector 108 may be located to face the X-ray
generator 106. The X-ray detector 108 may include a plurality of
X-ray detection elements. A single X-ray detection element may form
a single channel, but is not limited thereto.
[0086] The X-ray detector 108 may detect the X-rays generated by
the X-ray generator 106 and transmitted through the object 10, and
generate an electric signal to correspond to the intensity of the
detected X-rays.
[0087] The X-ray detector 108 may include an indirect-type detector
for detecting radiation by converting the radiation to light, and a
direct-type detector for detecting radiation by converting the
radiation directly to charges. The indirect-type X-ray detector may
use a scintillator. The direct-type X-ray detector may use a photon
counting detector. A Data Acquisition System (DAS) 116 may be
connected to the X-ray detector 108. An electric signal generated
by the X-ray detector 108 may be collected by the DAS 116. The
electric signal generated by the X-ray detector 108 may be wiredly
or wirelessly collected by the DAS 116. Furthermore, the electric
signal generated by the X-ray detector 108 may be provided to an
analog-to-digital converter (not shown) through an amplifier (not
shown). Data output from the X-ray detector 108 is called raw
data.
[0088] Depending on the slice thickness or the number of slices,
only a part of data collected from the X-ray detector 108 may be
provided to an image processor 126, or the image processor 126 may
select only a part of data.
[0089] Such a digital signal may be provided to the image processor
126 through the data transmitter 120. The digital signal may be
wiredly or wirelessly transmitted to the image processor 126
through the data transmitter 120.
[0090] The controller 118 in accordance with an embodiment of the
present disclosure may control operation of the respective modules
of the CT scanner 100. For example, the controller 118 may control
operation of the table 105, rotation driver 110, collimator 112,
DAS 116, storage 124, image processor 126, input unit 128, display
unit 130, communication unit 132, etc.
[0091] The image processor 126 may receive the data obtained from
the DAS 116, e.g., data before processing, through the data
transmitter 120, and perform pre-processing on the data.
[0092] Pre-processing may include, for example, a process of
correcting non-uniform sensitivity between channels, or a process
of correcting signal loss due to a drastic decrease in signal
intensity or due to an X-ray absorbent like metal.
[0093] Resultant data pre-processed by the image processor 126 may
be referred to as projection data. The projection data may be
stored in the storage 124 together with scanning conditions in data
acquisition (e.g., tube voltage, scanning angle, etc.).
[0094] The projection data may be a set of raw data scanned at one
scanning angle. In other words, a set of raw data simultaneously
obtained at the same scanning angle for all the channels is called
the projection data.
[0095] The storage 124 may include storage media in at least one
type of flash memory, hard disk, multimedia card micro type memory,
card type memory (e.g., SD or XD memory), Random Access Memory
(RAM), Static Random Access Memory (SRAM), Read-Only Memory (ROM),
Electrically Erasable Programmable Read-Only Memory (EEPROM),
Programmable Read-Only Memory (PROM), magnetic memory, magnetic
disk, and optical disk.
[0096] The image processor 126 may reconstruct a cross-sectional
image of an object using the obtained projection data. The scanned
image may be a 3D image. In other words, the image processor 126
may create a 3D image of an object in e.g., a cone beam
reconstruction method based on the obtained projection data.
[0097] External inputs, such as X-ray scanning conditions, image
processing conditions, etc., may be received through the input unit
128. For example, X-ray scanning conditions may include a plurality
of tube voltages, a plurality of X-ray energy value settings, a
selection of scanning protocols, a selection of image
reconstruction methods, FOV area settings, the number of slices,
slice thickness, image post-processing parameter settings, etc.
Image processing conditions may include the resolution of an image,
attenuation coefficient settings of an image, image combination
ratio settings, etc.
[0098] The input unit 128 may include e.g., a device for receiving
certain inputs from outside. For example, the input unit 128 may
include a microphone, a keyboard, a mouse, a joystick, a touch pad,
a touch pen, a voice or gesture recognition device, etc.
[0099] The display unit 130 may display an X-ray scanned image
reconstructed by the image processor 126.
[0100] Exchanges of data, power, etc., among the aforementioned
elements may be performed using at least one of wired, wireless,
and optical communications.
[0101] The communication unit 132 may perform communication with
external devices, external medical devices, etc., through a server
134. This will be further described below in connection with FIG.
3.
[0102] FIG. 3 shows an arrangement of a communication unit.
[0103] The communication unit 132 may be connected to a network 301
via cable or wirelessly for communicating with the external server
134, a medical equipment 136, or a portable device 138. The
communication unit 132 may exchange data with a hospital server or
another medical equipment in the hospital through the Picture
Archiving and Communication System (PACS).
[0104] Furthermore, the communication unit 132 may perform data
communication with the portable device 138 according to the Digital
Imaging and Communications in Medicine (DICOM) standard.
[0105] The communication unit 132 may transmit or receive data
related to diagnosis of an object over the network 301. The
communication unit 132 may also transmit or receive medical images
obtained by the medical equipment 136, such as an MRI device, an
X-ray scanner, etc.
[0106] Furthermore, the communication unit 132 may receive a
patient's medical history or treatment schedule from the server 134
and use them for a clinical diagnosis of the patient. The
communication unit 132 may further perform data communication not
only with the server 134 or medical equipment 136 in the hospital
but also with the portable device 138 of the user or the
patient.
[0107] Moreover, the communication unit 132 may transmit
information about whether an equipment is malfunctioned and about
the state of quality management to a system manager or service
person and receive feedback over a network.
[0108] All imaging devices have spatial resolution. The spatial
resolution refers to precision of an image scanned by driving an
imaging device to scan an object in a space. The image obtained
from the imaging device may not perfectly represent a state of the
object at the scanning point in time without blurring, due to the
nature of the imaging device. For example, due to the movement of
the imaging device itself while the imaging device is being driven,
the movement may appear in a scanned image itself. Thus, the
spatial resolution is determined by the extent of blurring that
occurs in the image. For example, an imaging device having high
spatial resolution has a less extent of blurring in its image
compared to an imaging device having low spatial resolution.
[0109] The tomography apparatus has the spatial resolution as well.
A limitation on the spatial resolution of the tomography apparatus
causes blurring artifacts in a scanned image. Such a blurring
artifact in a scanned image degrades image quality of the scanned
image. This causes the user, e.g., a doctor, to read the image
incorrectly and thus diagnose an illness inaccurately. For example,
if a blurring artifact is created in a part of the image, which
represents a calcium region, a blood vessel not actually clogged
might look clogged. This may thus drop the accuracy in diagnosis of
vascular disease.
[0110] The blurring artifact may be improved by estimating a Point
Spread Function (PSF) and de-blurring the image based on the
estimated PSF. The PSF varies depending on the tomography
apparatus. Specifically, the PSF may vary depending on product
specifications and/or performance of the tomography apparatus. The
PSF has a complex form, and may vary with a position of the object
formed within the gantry and a tube current measured in mill
amperes for X-ray generation. Correcting the blurring artifact may
be hereinafter referred to as de-blurring or de-blooming. For
convenience of explanation, correcting the blurring artifact will
now be collectively called `de-blurring`.
[0111] In de-blurring an image based on a PSF, unless the PSF is
accurately estimated, the image may be obtained with some blurred
part not perfectly eliminated. Furthermore, in a de-blurred image,
artifacts like undershooting or overshooting may be created.
[0112] In general, in estimating the PSF of the tomography
apparatus, a single PSF is estimated and used. Specifically, a
scanned image or reconstructed image is de-blurred by applying a
single specified PSF for a particular tomography apparatus.
[0113] If an image is de-blurred based on the same PSF for all the
positions within an FOV, the PSF may not be accurate for some
positions. Furthermore, in case of de-blurring an image for which
pre-processing and reconstruction has already been completed,
inaccurate de-blurring may be performed on the entire image in that
de-blurring is performed even on unnecessary information deleted or
added in the step of reconstruction. Accordingly, an image may be
obtained with some blurred part not perfectly eliminated, or some
artifacts, such as undershooting or overshooting may be created in
the image.
[0114] However, even within the FOV of the particular tomography
apparatus, the PSF may vary depending on the position of the
object. Furthermore, even with the projection data used in the step
of image pre-processing, the PSF may be estimated and de-blurring
may be performed.
[0115] Accordingly, in an embodiment of the present disclosure, the
projection data is used to predict and use different PSFs depending
on the position of an object formed within the gantry of the
tomography apparatus. In other words, to estimate an accurate PSF,
projection data is used to estimate a different PSF depending on
the position of the object.
[0116] FIG. 4 shows views for explaining the need of accurate PSF
estimation.
[0117] Referring to FIG. 4, initial images 401, 411 represent
images before de-blurring. Parts that represent outlines of an
object appear blurred in the initial image 401, due to blurring
artifacts in the initial image 401. Referring to an area 421 shown
in FIG. 4, outlines of the object are not represented with a clear
gray level but with a plurality of gray levels having similar
values, and thus the outline parts are not clearly imaged.
[0118] A de-blurred image 402 in FIG. 4 is an image de-blurred
based on an inaccurate PSF. In this case, parts that represent
outlines of an object 403 in the de-blurred image 402 appears clear
compared to the initial image 401. However, an artifact in the form
of a white band is created on parts 404 that represent outermost
edges of the object 403.
[0119] Therefore, to effectively improve the blurring artifact in
tomographic scanning of an object, a process of de-blurring an
image based on an accurately estimated PSF is required.
[0120] In embodiments of the present disclosure, blurring artifacts
created in an image may be effectively improved by de-blurring
based on projection data and a different PSF depending on the
position of the object formed within the gantry of a tomography
apparatus.
[0121] FIG. 5A is a block diagram of a tomography apparatus,
according to an embodiment of the present disclosure.
[0122] Referring to FIG. 5A, a tomography apparatus 500 in
accordance with an embodiment of the present disclosure includes a
controller 510, an image processor 520, and a storage 530. The
tomography apparatus 500 refers to any electronic device capable of
performing tomographic scanning to obtain, reconstruct and/or
display a scanned image.
[0123] The tomography apparatus 500 may be included in the CT
scanner 100 as described above in connection with FIGS. 1 and 2. In
this case, the controller 510, image processor 520, and storage 530
may correspond to the controller 118, image processor 126, and
storage 124 shown in FIG. 2, respectively. Furthermore, the
tomography apparatus 500 may be included in the medical equipment
136 or portable device 138 as described in FIG. 3, and may operate
while being connected to the CT scanner 100.
[0124] The controller 510 in accordance with an embodiment of the
present disclosure may obtain a PSF varying with the position
within a FOV formed in the gantry.
[0125] The PSF may be fetched from outside of the tomography
apparatus. Alternatively, in the tomography apparatus, a plurality
of sample images may be obtained by scanning a sample object (e.g.,
a phantom) at a plurality of different positions, and a plurality
of PSFs corresponding to the plurality of positions may be
estimated.
[0126] FIGS. 5B and 5C are detailed views of an FOV area shown in
FIG. 2. In FIG. 5B, the same features as in FIG. 2 are represented
with the same reference numerals.
[0127] Referring to FIGS. 5B and 5C, in an embodiment of the
present disclosure, scanning is performed by placing a sample
object at each of different positions 511, 512, 513 included within
a FOV 501. Accordingly, the tomography apparatus 500 obtains a
plurality of sample projection data for the plurality of different
positions 511, 512, 513. Although a plurality of different
positions are illustrated as the positions 511, 512, 513 in FIGS.
5B and 5C, they may be set to other various positions in addition
to the illustrated positions in other embodiments. Furthermore,
although the plurality of positions 511, 512, 513 at which the
sample object may be located do not overlap each other in FIGS. 5B
and 5C, some or all of the positions 511, 512, 513 may overlap in
other embodiments.
[0128] Referring to FIG. 5B, the positions 511, 512, 513 of the
sample object may be represented by distances from the X-ray
generator 106 (i.e., distances from a radiation focal point). If
points located at the same distance from the X-ray generator 106 in
the FOV are defined to be in a single band, the position 511 of a
first sample object, the position 512 of a second sample object,
and the position 513 of a third sample object may be represented to
correspond to a first band B1, a second band B2, and a third band
B3, respectively.
[0129] The controller 510 may determine positions of the respective
sample objects based on a plurality of sample scanned images
corresponding to the plurality of bands, and estimate PSFs
corresponding to the positions of the respective sample objects
based on the sample projection data of the respective sample
objects.
[0130] For example, when a sample object is located on the position
511 on the first band B1, the controller 510 determines that the
sample object is located on the first band B1 using a first sample
scanned image obtained by tomographic scanning, and estimates a
first PSF for the first band B1 based on the first sample
projection data.
[0131] Also, when a sample object is located on the position 512 on
the second band B2, the controller 510 may determine that the
sample object is located on the second band B2 using a second
sample scanned image obtained by tomographic scanning, and estimate
a second PSF for the second band B2 based on the second sample
projection data. In the same way, the controller 510 may determine
that a sample object is located on the third band B3 using a third
sample scanned image and estimate a third PSF for the third band B3
based on the third sample projection data.
[0132] In this case, the positions 511, 512, 513 (on the bands B1,
B2, B3) may be represented by y coordinates, and the controller 510
may estimate corresponding PSFs for the respective y
coordinates.
[0133] Moreover, referring to FIG. 5C, the positions 511, 512, 513
of the sample objects may be represented by corresponding single
device beam channel values. If points located at the same channel
in the FOV are defined to be in a single beam line, the position
511 of the first sample object, the position 512 of the second
sample object, and the position 513 of the third sample object may
be represented to correspond to a first beam line L1, a second beam
line L2, and a third beam line L3, respectively.
[0134] The controller 510 may determine positions of the respective
sample objects based on a plurality of sample scanned images
corresponding to the plurality of beam lines L1, L2, L3, and
estimate PSFs corresponding to the positions of the respective
sample objects based on the sample projection data of the
respective sample objects.
[0135] For example, when a sample object is located at the position
511 in the first beam line L1, the controller 510 may determine
that the sample object is located in the first beam line L1 using
the first sample scanned image obtained by tomographic scanning,
and estimate a fourth PSF for the first beam line L1 based on the
first sample projection data, and when a sample object is located
at the position 512 in the second beam line L2, the controller 510
may determine that the sample object is located in the second beam
line L2 using the second sample scanned image obtained by
tomographic scanning, and estimate a fifth PSF for the second beam
line L2 based on the second sample projection data. In the same
way, the controller 510 may determine that a sample object is
located in the third beam line L3 using a third sample scanned
image and estimate a sixth PSF for the third beam line L3 based on
the third sample projection data.
[0136] In this case, the positions 511, 512, 513 (in the beam lines
L1, L2, L3) may be represented by x coordinates, and the controller
510 may estimate corresponding PSFs for the respective x
coordinates.
[0137] Moreover, referring both to FIGS. 5B and 5C, the positions
511, 512, 513 of the sample objects may be represented by distances
from the X-ray generator 106 and single device beam channel values.
The positions 511, 512, and 513 of the first, second, and third
sample objects may be represented to correspond to the first band
B1 and first beam line L1, the second band B2 and second beam line
L2, and the third band B3 and third beam line L3, respectively.
[0138] The controller 510 may estimate a plurality of PSFs
corresponding to a plurality of positions, based on a plurality of
sample projection data corresponding to the plurality of bands B1,
B2, B3 and plurality of beam lines L1, L2, L3.
[0139] In this case, the positions 511, 512, 513 of the first to
third sample objects may be represented by combinations of x
coordinates (x1, x2, x3) and y coordinates (y1, y2, y3), and the
controller 510 may estimate corresponding PSFs for the respective
xy coordinates.
[0140] Furthermore, the controller 510 may estimate a plurality of
PSFs corresponding to beam angles formed by cone beams or fan
beams.
[0141] Moreover, the controller 510 may estimate a PSF using
interpolation or extrapolation even for a point at which no sample
object is located.
[0142] In addition, in estimating PSFs, the controller 510 may
estimate the PSFs in the form of a Gaussian function over distance.
How to estimate the PSF, however, is not limited to the estimation
in the form of the Gaussian function.
[0143] The controller 510 may estimate PSFs in a mathematical
method as well. For example, the controller 510 may estimate PSFs
by extracting edge information from projection data,
differentiating the result of extraction, and performing Fourier
transform.
[0144] How to estimate the PSF will be described in detail later in
connection with FIG. 8.
[0145] The plurality of PSFs estimated by the controller 510 may be
stored in the storage 530. Specifically, the tomography apparatus
500 may store a plurality of PSFs in the storage 530 in advance. In
this case, the storage 530 may store the PSFs corresponding to
various geometric information. In this regard, the controller 510
may fetch a PSF for a position (in a band and beam line) of the
object based on the plurality of PSFs stored in the storage
530.
[0146] A process of estimating and storing the plurality of PSFs in
the storage 530 may be performed in the initial procedure of the
tomography apparatus 500. Alternatively, the process may be
performed in the process of calibration after internal parts of the
tomography apparatus 500 are replaced. However, it is not limited
thereto.
[0147] The storage 530 in accordance with an embodiment of the
present disclosure may store the plurality of PSFs in the form of a
table, but is not limited thereto.
[0148] The image processor 520 in accordance with an embodiment of
the present disclosure may obtain projection data for which image
pre-processing has been performed, by de-blurring projection data
of an object scanned within the FOV based on PSFs corresponding to
the respective positions, which are estimated by the controller
510. Specifically, the projection data may be de-blurred by
performing deconvolution on the projection data based on estimated
PSFs for the respective positions. De-blurring includes performing
de-blurring by means of a Wiener filter. Deconvolution of an image
is widely known to ordinary people in the art, so the description
will be omitted herein.
[0149] The image processor 520 in accordance with an embodiment of
the present disclosure may obtain projection data corresponding to
the respective rotation angles by scanning the object at various
angles along a rotating path of the gantry, and the aforementioned
de-blurring may be performed on each projection data.
[0150] A process of performing de-blurring will be described later
in connection with FIG. 10.
[0151] Referring to FIG. 6, a process for the controller 510 to
determine a position of an object based on a cross-sectional image
will be described in detail.
[0152] FIG. 6 is a view for cross-sectional images of an object,
which are created at different rotation angles.
[0153] Referring to FIG. 6, when an object (ob) is located at a
position within an FOV, the position 511 of the object (ob) may
vary with the rotation angle of the gantry. In this case, the image
processor 520 may obtain a first scanned image I1 corresponding to
the rotation angle of 0 degree, and a second scanned image I2
corresponding to the rotation angle of 30 degrees. Of course, other
scanned images corresponding to various rotation angles may be
obtained. The first and second scanned images I1 and I2 may be
cross-sectional images in which brightness level is represented in
gray scale.
[0154] The controller 510 may determine a beam line and a band of
the object (ob) at a rotation angle based on position information
of the object (ob) appearing in the cross-sectional image.
[0155] Specifically, the controller 510 may determine x and y
coordinates of a center position of an area in the first and second
scanned images I1 and I2, which has brightness levels higher than a
threshold to be a position of the object (ob).
[0156] The controller 510 may then determine a beam line and band
information based on the x coordinate and the y coordinate,
respectively, of the object (ob) that appears in the first scanned
image I1. If a value x1 corresponds to the first beam line L1 and a
value y1 corresponds to the first band B1, the controller 510 may
determine that the object (ob) is located in the first beam line L1
and first band B1 at the rotation angle of 0 degree.
[0157] The controller 510 may also determine a beam line and a band
based on the x coordinate and the y coordinate, respectively, of
the object (ob) that appears in the second scanned image I2. If a
value x2 corresponds to the second beam line L2 and a value y2
corresponds to the second band B2, the controller 510 may determine
that the object (ob) is located in the second beam line L2 and
second band B2 at the rotation angle of 30 degrees.
[0158] The image processor 520 may also obtain cross-sectional
images at other rotation angles, and the controller 510 may
determine beam lines and bands of the object (ob) corresponding to
the respective rotation angles.
[0159] With the use of this beam line and band determination
method, the image processor 520 may obtain cross-sectional images
and projection data of a sample object located at different
positions, and accordingly, the controller 510 may estimate PSFs
corresponding to the respective positions of the sample object.
[0160] The PSF will now be described in more detail with reference
to FIGS. 7 and 8.
[0161] FIG. 7 is a view for explaining PSF.
[0162] The PSF is a function that represents a spatial response of
an image scanning device to a point. In other words, the PSF
corresponds to a spatial impulse response of the image scanning
device. The PSF herein may be approximated to a Gaussian
function.
[0163] Referring to FIG. 7, a wave for imaging a point 611 of an
object may be propagated from the X-ray generator 160. For example,
a wave reaching the point 611 of the object may be irradiated from
the point 611. As for a CT scanner, the wave may be an X-ray.
[0164] Such a wave may be obtained by an X-ray detector and
represented on a projection data plane 620, in which case, since
the point 611 of the object is not a point but has a definite area,
it may be represented as an area 621 in the projection data plane
620 detected by the X-ray detector.
[0165] Furthermore, artifacts 622 may appear in the projection data
plane 620. The artifacts 622 may be blurring artifacts.
[0166] FIG. 8 shows views for explaining PSF.
[0167] In FIG. 8, (a) shows an image 700 representing an area of an
object that appears on the projection data plane. Arbitrary
rectangular coordinates may be set in the image 700. For example,
the x-axis may be set to go across an area 706 of an object while
the y-axis may be set to be adjacent to the area 706.
[0168] Referring to (b) of FIG. 8, the x-axis represents positions
in a space, and v-axis represents pixel values for the respective
positions. A graph 710 shown in (b) of FIG. 8 represents pixel
values of a linear line 704 included in the image 700 when there is
no blurring artifact created in the image 700.
[0169] In the graph 710 shown in (b) of FIG. 8, negative values of
the x-coordinate correspond to a left area 702 while positive
values of the x-coordinate correspond to a right area 703. The
origin corresponds to a point 705 belonging to a surface 701. In
this example of the graph 710, for negative x-coordinate values,
pixel values are zero, while for positive x-coordinate values,
pixel values correspond to `a`. Accordingly, it can be seen that
the image has sharp outlines when the x-coordinates are zero.
[0170] Furthermore, a graph 720 shown in (b) of FIG. 8 is obtained
by transforming the graph 710 with a predefined PSF. The predefined
PSF may represent a PSF that exists in the tomography
apparatus.
[0171] In the graph 720, pixel values may gradually change around
the x-coordinate of zero, due to the PSF of the tomography
apparatus. Accordingly, the tomography apparatus may hardly obtain
outlines from the linear image 720.
[0172] In FIG. 8, (c) shows views for explaining an effect of
blurring artifacts.
[0173] Referring to (c) of FIG. 8, a graph 730 represents original
brightness levels of the object without blurring artifact.
[0174] A graph 740 shown in (c) of FIG. 8 represents a PSF of the
tomography apparatus. There is a blurring artifact in the graph
740, which appears in the form of an impulse.
[0175] As the tomography apparatus scans the object, the PSF of the
tomography apparatus is applied, and projection data 750 with a
blurring artifact may be obtained. Specifically, the tomography
apparatus may obtain the graph 750 with the blurring artifact by
convolution of the graph 730 and graph 740.
[0176] The tomography apparatus may obtain its PSF by obtaining the
projection data 730 without blurring artifact and the projection
data 750 with the PSF applied.
[0177] The projection data 730 without blurring artifact may be
obtained by scanning, for example, with a thin substance, such as a
thin wire or rod placed within the FOV.
[0178] There may be other various methods for estimating the PSF.
For example, the tomography apparatus may have stored information
about an original outline of the object (e.g., geometrical
information), and may mathematically estimate the PSF based on the
information. However, it is not limited thereto.
[0179] The tomography apparatus may receive information regarding
the original form of the outline of the object from the outside of
the apparatus. The information regarding the original form of the
outline may be information having pixel values drastically changing
around the x-coordinate of zero, as represented in the graph
710.
[0180] The tomography apparatus may also obtain the entire
projection data from scanning of the object. The tomography
apparatus may obtain a first area with less movement from the
entire projection data. The tomography apparatus may obtain
information regarding an outline of the object scanned in the first
area. For example, the information regarding the outline of the
scanned object may be information having pixel values slowly
changing around the x-coordinate of zero, as represented in the
graph 720. The tomography apparatus may estimate the PSF based on
the information regarding the outline of the scanned object and the
information regarding the original form of the outline.
[0181] Specifically, the PSF may be estimated by convolution of the
inverse of the projection data 730, which is the information about
the original form of the outline, and the projection data 750,
which is the information about the outline of the scanned
object.
[0182] How to estimate the PSF will now be described in detail with
reference to FIG. 9. FIG. 9 is a view for explaining how to
estimate a PSF.
[0183] Referring to FIG. 9, an image 800 is an image of projection
data obtained by scanning a sample object having the form of a
ball, rod, or bar. The horizontal axis and vertical axis of the
image 800 represent positions of pixels that make up the image 800.
For example, the image 800 may correspond to a 2D plane, which is
an FOV plane. In this regard, due to the PSF of the tomography
apparatus, blurring artifacts 801 may be created in the image
800.
[0184] The controller 510 in accordance with an embodiment of the
present disclosure may measure a distribution of brightness levels
with respect to a position 802 of a particular pixel that exists in
a reference line 803 set in the image 800. Specifically, the
brightness levels may be represented in Hounsfield Unit (HU)
values. In this regard, the distribution 812 of HU values may
appear in the form of a Gaussian function.
[0185] The controller 510 may estimate a PSF 811 at the particular
position 802 based on the distribution 812 of HU values. The
estimated PSF 811 may also appear in the form of a Gaussian
function.
[0186] If the image processor 520 in accordance with an embodiment
of the present disclosure obtains a plurality of sample projection
data by scanning the sample object at a plurality of different
positions (i.e., in a plurality of different beam lines and a
plurality of different bands) within the gantry of the tomography
apparatus, the controller 510 may determine the positions of the
sample object and estimate PSFs for the respective positions of the
sample object. A detailed method for determining the positions of
the sample object was described above in connection with FIG. 6 and
a detailed method for estimating the PSF was described above in
connection with FIGS. 7 to 9, so the description of the methods
will be omitted herein.
[0187] For example, the controller 510 may estimate a PSF
corresponding to the first band and first beam line based on first
sample projection data (P1, P1') of the sample data located in the
first band and first beam line.
[0188] The controller 510 may also estimate a PSF corresponding to
the second band and second beam line based on second sample
projection data (P2, P2') of the sample data located in the second
band and second beam line.
[0189] The projection data scanned in different beam lines and
different bands may have the blurring artifacts 810 in different
forms in the image. Accordingly, the distributions of HU values may
appear differently, and the PSFs estimated based on the
distribution of HU values may appear differently depending on the
beam lines and the bands.
[0190] FIG. 10 shows views for explaining a plurality of PSFs
corresponding to a plurality of beam lines and bands.
[0191] Referring to (a) of FIG. 10, a plurality of impulses 901,
902, 903 represented in a graph 900 indicate a plurality of PSFs
estimated by the controller 510.
[0192] In (a) of FIG. 10, the horizontal axis corresponds to beam
line information within an FOV, and the vertical axis corresponds
to distances from the X-ray generator 106 within the FOV, i.e.,
distances r from a radiation focal point.
[0193] The more estimated PSFs there are, the more accurately the
controller 510 may eliminate blurring artifacts based on the PSFs.
The controller 510 may estimate a PSF using interpolation or
extrapolation even for a point not actually measured.
[0194] Beam lines and bands for which PSFs are estimated may be
changed by settings. Furthermore, beam lines and bands for which
PSFs are estimated may be selected to cover as many areas within
the gantry as possible.
[0195] Referring to (b) of FIG. 10, the controller 510 may generate
a plurality of PSFs 911, 912 based only on information about the
band, i.e., a distance r from the X-ray generator 106. In FIG. 10,
(b) shows a graph 910 of the PSFs generated based on the band, with
less amount of data to be stored as compared to (a) of FIG. 10.
[0196] In this case, as a plurality of different objects are
scanned in the same band regardless of the beam lines, the same PSF
may be applied to the plurality of objects during de-blurring.
[0197] Similarly, although not shown, the controller 510 may
generate a plurality of PSFs 921, 922 based only on information x
about beam lines, in which case, as a plurality of different
objects are scanned in the same beam line regardless of the bands,
the same PSF may be applied to the plurality of objects during
de-blurring.
[0198] Furthermore, referring to (c) of FIG. 10, the controller 510
may generate the PSFs 921, 922 for each area by grouping the
plurality of bands and plurality of beam lines.
[0199] In this case, the controller 510 may obtain representative
PSFs 921, 922 of the grouped regions of interest ROI1, ROI2. Here,
the representative PSF may be a PSF existing in the center of the
region of interest. In performing de-blurring, for the objects
located in fourth to sixth bands y4 to y6, and first to third beam
lines x1 to x3, a PSF 921 for the fifth band y5 and the second beam
line x2 is applied as a representative PSF of the first region of
interest ROI1, and for the objects located in second to fourth
bands y2 to y4, and first to third beam lines x1 to x3, a PSF 922
for the second band y2 and the second beam line x2 may be applied
as a representative PSF of the second region of interest R012.
De-blurring will be described in more detail later.
[0200] As such, once a PSF is estimated for each position, the
estimated PSF may be stored in the storage 530 (see FIG. 5A)
together with information about the position (band and beam line
information).
[0201] In the meantime, once a PSF is estimated for each position,
the tomography apparatus may further perform calibration to correct
the estimated PSF according to the location of the region of
interest (ROI).
[0202] For this, the tomography apparatus in another embodiment of
the present disclosure may further include an adaptive filter, and
FIG. 11 is a control block diagram of a tomography apparatus
further including the adaptive filter, in accordance with another
embodiment of the present disclosure.
[0203] The tomography apparatus in accordance with another
embodiment includes a controller 501, an adaptive filter 515, an
image processor 520, and a storage 530.
[0204] The controller 501, image processor 520, and storage 530 are
the same as the controller 501, image processor 520, and storage
530 described above in connection with FIG. 5A, so the overlapping
description will be omitted.
[0205] If a PSF generated by the controller 510 is called a first
PSF, the adaptive filter 515 corrects the first PSF according to
the location of the region of interest ROI estimated by the
controller 510.
[0206] For example, the adaptive filter 515 may generate a second
PSF having the same or different value depending on a distance to
the region of interest ROI from the isocenter (ISO) within or of an
SFOV and a distance from the X-ray generator 106 (i.e., a distance
from a radiation focal point), and generate a corrected PSF by
convolution of the first PSF and the second PSF. The distance from
the isocenter ISO of the region of interest ROI may correspond to a
beam line located in the region of interest ROI, and the distance
from the X-ray generator 106 may correspond to a band located in
the region of interest ROI.
[0207] FIG. 12 is a view for explaining a method for an adaptive
filter to generate a second PSF.
[0208] Let a point of the center of an SFOV be the isocenter ISO, a
beam line in the SFOV that forms a maximum irradiation angle
.gamma..sub.c from the optic axis l.sub.c of an X-ray irradiated by
the X-ray generator 106 be a maximum angle beam line l.sub.MAX, and
an angle formed by a beam line l.sub.k-2 corresponding to an X-ray
element k-2 with respect to the optic axis be an element angle
.gamma..sub.k-2, the adaptive filter 515 may generate the second
PSF in the following equation 1:
psf ( i ) = exp ( - ( ( .gamma. i - .gamma. c ) 2 2 .sigma. 2 ) ( 1
) ##EQU00001##
where i denotes a number of an X-ray detection element for
receiving an X-ray from the X-ray generator 160, .gamma..sub.i
denotes an element angle of a beam line corresponding to the
i.sup.th detector element, .gamma..sub.c denotes a maximum
irradiation angle, and .sigma. may be represented by the following
equation 2:
.sigma. 2 = .sigma. d 2 + .sigma. f 2 .sigma. d = Det Size 2 2 ln 2
L FCD .sigma. f = .sigma. c FDD - L L .sigma. c = .sigma. a cos 2
.gamma. C + .sigma. b sin 2 .gamma. C .sigma. a = a 2 2 ln 2 ,
.sigma. b = b 2 2 ln 2 ( 2 ) ##EQU00002##
[0209] where, a and b denote vertical and horizontal lengths of a
region of interest ROI for which the second PSF is to be generated,
respectively (see FIG. 12), DetSize denotes a detector pitch of one
or more detector elements for detecting X-rays, FDD denotes a
distance from an X-ray radiation focal point to a detector element
of the X-ray detector 108, FCD denotes a distance from the X-ray
radiation focal point (fp) of the X-ray generator 106 to the
isocenter ISO, and L denotes a distance from the X-ray radiation
focal point (fp) of the X-ray generator 106 to the region of
interest ROI.
[0210] `a` and `b` may be stored in the storage 530 in advance in
the initial process or in the calibration process, or may have
values set depending on the beam line and band, i.e., the region of
interest ROI. For example, a may have a value of 1.2 mm, and b may
have a value of 8.1 mm.
[0211] As such, the adaptive filter 515 may generate the second PSF
for each region of interest (ROI) and generate a corrected PSF by
convolution of the first and second PSFs. The corrected PSF may be
stored in the storage 530 and provided for the image processor 520
in de-blurring.
[0212] In the case of further including the adaptive filter 515, an
image having uniform resolution for all the regions of interest
within the SFOV may be obtained irregardless of the distance from
the isocenter ISO.
[0213] The adaptive filter 515 may be implemented together with the
image processor 520 in a single module. In this case, the image
processor 520 may correct the PSF for each location of the region
of interest ROI while performing de-blurring.
[0214] A method for the tomography apparatus to perform de-blurring
will now be described.
[0215] The tomography apparatus may perform de-blurring on an image
based on the stored PSF.
[0216] First, assuming that an object is located within an FOV, as
described above in connection with FIG. 6, the controller 510 may
determine a position where the object is located, i.e., a beam line
and band, based on a cross-sectional image of the object scanned at
a rotation angle.
[0217] The image processor 520 may then fetch a PSF corresponding
to the beam line and band of the object from the storage 530, and
mathematically calculate the inverse PSF based on the fetched PSF.
The image processor 520 may estimate projection data without
blurring artifact by convolution of the inverse PSF and projection
data with a blurring artifact.
[0218] Alternatively, the image processor 520 may estimate
projection data without blurring artifact by deconvolution of
projection data with a blurring artifact and the PSF.
[0219] FIG. 13 is a mimetic diagram of a sinogram, a set of a
plurality of projection data.
[0220] Given that a set of projection data is called a sinogram,
referring to FIG. 13, the sinogram may include projection data in
the range of rotation angles between 0 to 360 degrees.
[0221] The image processor 520 in accordance with an embodiment of
the present disclosure may obtain projection data of an object at
each rotation angle of the gantry, and perform de-blurring on the
projection data based on the PSF corresponding to a position of the
object, i.e., a beam line and band in which the object is
located.
[0222] In this case, the image processor 520 may also perform
de-blurring for a plurality of regions of interest (ROI) based on
respective PSFs corresponding to the plurality of regions of
interest ROI of the projection data scanned at a rotation angle of
the gantry.
[0223] The PSF used in de-blurring may be the PSF before correction
as described above in connection with FIG. 10, or the PSF after
correction as described above in connection with FIG. 11.
[0224] De-blurring may be performed for all of the plurality of
projection data corresponding to a plurality of rotation angles,
e.g., 0, 10, . . . , 350, 360 degrees. In other words, since
corresponding beam lines x1, x2, . . . and bands y1, y2, . . . for
the respective rotation angles are different, different PSFs may be
applied for the respective rotation angles.
[0225] Furthermore, the image processor 520 may perform back
projection based on the plurality of projection data, i.e., the
sinogram, for which de-blurring has been performed. Back projection
will further be described later. As a result of de-blurring and
back projection, a scanned image with the blurring artifact
eliminated may be produced.
[0226] The image processor 520 may also perform post image
processing on the scanned image. For example, the image processor
520 may filter noise components from the scanned image.
[0227] FIG. 14 is a view for explaining a back projection process
performed by an image processor. An X-ray generator 1011 to 1014
shown in FIG. 14 is the same as the X-ray generator 160 as shown in
FIG. 2.
[0228] The image processor 520 may perform back projection based on
the plurality of projection data, i.e., the sinogram.
[0229] Referring to (a) of FIG. 14, as the X-ray generator 1011,
1012, 1013, 1014 irradiates X-rays onto an object (ob) at various
rotation angles, projection data 1021, 1022, 1023, 1024
corresponding to the respective rotation angles may be generated.
In case of representing the projection data 1021, 1022, 1023, 1024
as images 1031, 1032, 1033, 1034, an overlapping region 1040 is
formed, and the region 1040 becomes a transmitted image 1050
corresponding to the object (ob). As shown in (a) of FIG. 14, if
the image processor 520 performs back projection without performing
de-blurring, the transmitted image 1050 of the object is not
accurately represented due to blurring artifacts.
[0230] However, referring to (b) of FIG. 14, as the X-ray generator
1111, 1112, 1113, 1114 irradiates X-rays onto the object (ob) at
various rotation angles, projection data corresponding to the
respective rotation angles is created, and projection data (1121,
1122, 1123, 1124) for which de-blurring has been performed by
applying different PSFs depending on the positions (i.e., bands and
beam lines) of the respective projection data may be generated.
[0231] In case of representing the projection data 1121, 1122,
1123, 1124, for which de-blurring has been performed, as images
1131, 1132, 1133, 1134, an overlapping region 1140 is formed, and
the region 1140 becomes a scanned image 1150 corresponding to the
object (ob). As shown in (b) of FIG. 14, if the image processor
performs back projection based on the projection data for which
de-blurring has been performed, the scanned image 1150 of the
object with the blurring artifact eliminated may be created.
[0232] In this regard, the image processor 520 may use a full
reconstruction method to use scanned data obtained by one rotation
of the X-ray generator 1111, 1112, 1113, 1114 to be reconstructed
into the scanned image 1150. In addition, the image processor 520
may use a half reconstruction method to use scanned data obtained
by more than half a rotation but less than one rotation of the
X-ray generator 1111, 1112, 1113, 1114 to be reconstructed into the
scanned image 1150. The method for reconstructing a scanned image,
however, is not limited thereto.
[0233] Subsequently, the image processor 520 in accordance with an
embodiment of the present disclosure may filter noise components
from the scanned image 1150. Filtering the noise components may
employ noise filtering methods commonly known to the ordinary
people in the art, so the description will be omitted herein.
[0234] A display unit may output a screen containing a final
scanned image obtained by the image processor 520. The display unit
may also display a user interface screen required to proceed
scanning.
[0235] The display unit corresponds to the display unit 130 shown
in FIG. 2, so the overlapping description will be omitted.
[0236] FIG. 15 is a flowchart illustrating a method for controlling
a tomography apparatus, according to an embodiment of the present
disclosure.
[0237] Operational features of the method for controlling the
tomography apparatus in accordance with an embodiment of the
present disclosure are the same as those of the tomography
apparatus 100, 500 as described above with reference to FIGS. 1 to
14. Accordingly, in explaining the method for controlling the
tomography apparatus, the overlapping descriptions with those of
FIGS. 1 to 14 will be omitted.
[0238] Referring to FIG. 15, in the method for controlling a
tomography apparatus in accordance with an embodiment of the
present disclosure, a plurality of PSFs corresponding to a
plurality of positions are estimated based on a plurality of sample
projection data obtained by scanning a sample object at the
plurality of different positions, in step S1210. The operation of
step S1210 may be performed by the controller of the tomography
apparatus according to an embodiment of the present disclosure. In
this case, the position of the sample object may be manually input
by the user, or the controller may directly determine the position
based on a cross-section image (see FIG. 6).
[0239] In the method for controlling a tomography apparatus in
accordance with an embodiment of the present disclosure,
de-blurring is performed based on the PSFs corresponding to the
respective positions of the object and the projection data obtained
by scanning the object, in step S1220. In this case, the position
of the object may also be manually input by the user, or the
controller may directly determine the position based on a
cross-sectional image (see FIG. 6).
[0240] Specifically, performing deconvolution on the projection
data of the object based on the generated PSF, a blurring artifact
present in the projection data of the object may be improved. The
operation of step S1220 may be performed by the image processor of
the tomography apparatus according to an embodiment of the present
disclosure.
[0241] In the method for controlling a tomography apparatus in
accordance with an embodiment of the present disclosure, a final
scanned image is obtained by performing image reconstruction, such
as performing back projection based on a plurality of de-blurred
projection data, i.e., a sinogram, and filtering the noise
components, in step S1230. The plurality of de-blurred projection
data may be ones scanned at different rotation angles of the gantry
102 of the tomography apparatus 100. The operation of step S1230
may be performed by the image processor of the tomography apparatus
according to an embodiment of the present disclosure.
[0242] FIG. 16 is a flowchart illustrating a method for controlling
a tomography apparatus to explain operation of S1210 in detail.
[0243] Referring to FIG. 16, in the method for controlling a
tomography apparatus in accordance with an embodiment of the
present disclosure, a plurality of sample projection data are
obtained by scanning a sample object at a plurality of different
positions, in step S1310. In this case, the plurality of different
positions may each be defined with one of a plurality of bands and
one of a plurality of beam lines.
[0244] A band refers to a line formed by connecting positions at
the same distance from the X-ray generator 106, and a beam line
refers to a line formed by connecting positions located on the same
channel (i.e., on the same beam path) within the FOV.
[0245] The operation of step S1310 may be performed by the
controller of the tomography apparatus according to an embodiment
of the present disclosure.
[0246] In the method for controlling a tomography apparatus in
accordance with an embodiment of the present disclosure, a band or
beam line in which the sample object is located is determined based
on a cross-sectional image of the sample object, in step S1310.
[0247] The beam line or band in which the sample object is located
may be determined based on a relative location of a bright region
compared to the entire region in the cross-sectional image of the
sample object.
[0248] The operation of step S1320 may be performed by the
controller of the tomography apparatus according to an embodiment
of the present disclosure.
[0249] In the method for controlling a tomography apparatus in
accordance with an embodiment of the present disclosure, a PSF of
the sample object is estimated based on outline information of the
sample object and projection data of the sample object, in step
S1330.
[0250] The outline information of the sample object is information
regarding an original form of the sample object, e.g., information
fetched from outside of the tomography apparatus.
[0251] Specifically, in the method for controlling a tomography
apparatus, a PSF may be estimated by convolution of the inverse of
projection data regarding the original form of the outline and
projection data regarding the scanned outline of the object.
[0252] The operation of step S1330 may be performed by the
controller of the tomography apparatus according to an embodiment
of the present disclosure.
[0253] In the method for controlling a tomography apparatus in
accordance with an embodiment of the present disclosure, the
information about the band or beam line of the estimated PSF is
stored with the estimated PSF, in step S1340.
[0254] For example, information about a band corresponding to the
estimated PSF among the plurality of bands and the estimated PSF
may be mapped and stored. Furthermore, information about a beam
line corresponding to the estimated PSF among the plurality of beam
lines and the estimated PSF may be mapped and stored. Moreover, the
information about a band corresponding to the estimated PSF among
the plurality of bands and the information about a beam line
corresponding to the estimated PSF among the plurality of beam
lines are mapped together to the estimated PSF and stored.
[0255] The operation of step S1340 may be performed by the
controller of the tomography apparatus according to an embodiment
of the present disclosure, and the information about the band or
beam line for the estimated PSF may be stored with the estimated
PSF in the storage.
[0256] In another embodiment, the tomography apparatus may further
include an adaptive filter, and the method for controlling a
tomography apparatus in accordance with an embodiment of the
present disclosure may further include correcting PSFs for
different locations of regions of interest ROI estimated by the
controller, i.e., different locations of the sample object. This
was described above in connection with FIGS. 11 and 12, so the
description is omitted herein.
[0257] FIG. 17 is a flowchart illustrating a method for a
tomography apparatus to perform image processing based on estimated
PSFs.
[0258] Referring to FIG. 17, in a method for controlling a
tomography apparatus in accordance with an embodiment of the
present disclosure, a cross-sectional image of an object scanned at
a position is obtained, in step S1410. The image processor of the
tomography apparatus may obtain a cross-sectional image at the
rotation angle of 0 degree.
[0259] The operation of step S1410 may be performed by the image
processor of the tomography apparatus according to an embodiment of
the present disclosure.
[0260] In the method for controlling a tomography apparatus in
accordance with an embodiment of the present disclosure, a band or
beam line in which the object is located is determined based on the
obtained cross-sectional image of the object, in step S1420.
[0261] In the method, the beam line or band in which the object is
located may be determined based on a relative location of a bright
region compared to the entire region in the cross-sectional
image.
[0262] The operation of step S1420 may be performed by the
controller of the tomography apparatus according to an embodiment
of the present disclosure.
[0263] In the method for controlling a tomography apparatus in
accordance with an embodiment of the present disclosure, projection
data of the object is de-blurred based on the determined band or
beam line in which the object is located, in step S1430. The
projection data may be obtained by the image processor.
[0264] Specifically, in the method for controlling a tomography
apparatus in accordance with an embodiment of the present
disclosure, a blurring artifact created in the projection data may
be improved by fetching a PSF from the storage corresponding to the
determined band or beam line in which the object is located and
performing deconvolution on the projection data of the object based
on the PSF.
[0265] The operation of step S1430 may be performed by the image
processor of the tomography apparatus according to an embodiment of
the present disclosure.
[0266] Although in the aforementioned embodiments, de-blurring is
performed only for the region of interest in which the object is
located, de-blurring may be performed even for the other regions of
interest where the object is not located.
[0267] Furthermore, although in the aforementioned embodiments, the
adaptive filter corrects the PSF depending on the different
location of the region of interest ROI estimated by the controller,
and the image processor performs de-blurring using the corrected
PSF, it is also possible for the image processor to correct the PSF
generated by the controller while performing de-blurring. In this
case, the image processor may correct the PSF depending on the
location of the region of interest.
[0268] In the method for controlling a tomography apparatus in
accordance with an embodiment of the present disclosure, projection
data of the object is obtained again at different rotation angles
in step S1460 until the X-ray generator completes a full round
turn, and de-blurring is performed on the projection data using the
PSF based on a relative position (i.e., a band or beam line) of the
object, which varies with the respective rotation angles.
[0269] Although step S1440 was described as using the full
reconstruction method by the tomography apparatus, the half
reconstruction method may be used as well, in which case projection
data of the object may be obtained until the X-ray generator turns
half a round, i.e., 180-degree turn.
[0270] In the method for controlling a tomography apparatus in
accordance with an embodiment of the present disclosure, in case of
obtaining a plurality of de-blurred project data, i.e., sinogram at
a plurality of rotation angles, an image is reconstructed based on
the plurality of de-blurred projection data, in step S1450.
[0271] For example, in the method for controlling a tomography
apparatus, noise components may be filtered from the scanned
image.
[0272] The operation of step S1450 may be performed by the image
processor of the tomography apparatus according to an embodiment of
the present disclosure.
[0273] According to embodiments of the present disclosure of a
tomography apparatus and method for controlling the same, blurring
artifacts created within a scanned image may be effectively
improved by generating different PSFs depending on the position of
an object.
[0274] Furthermore, according to embodiments of the present
disclosure of a tomography apparatus and method for controlling the
same, the blurring artifact created within the scanned image may be
accurately eliminated by generating a PSF and performing
de-blurring on projection data.
[0275] The aforementioned embodiments of the present disclosure may
be written into a program that may be executed by a computer, and
may be implemented in a universal digital computer for carrying out
the program using a computer-readable recording medium.
[0276] The computer-readable recording medium includes a storage
medium, such as magnetic storage medium (e.g., ROM, flopy disk,
hard disk, etc.), an optical medium (e.g., CD-ROM, DVD, etc.), and
carrier waves (e.g., transmission over the Internet).
Embodiments of the present disclosure have been described with
reference to accompanying drawings, but it is to be understood that
various modifications can be made without departing the scope of
the present invention.
[0277] While the disclosure has been shown and described with
reference to certain exemplary embodiments thereof, it will be
understood by those skilled in the art that various changes in form
and details may be made therein without departing from the spirit
and scope of the disclosure as defined by the appended claims and
their equivalents.
* * * * *